A Scoping Review of the Experiences of Violence and Abuse Among Sexual and Gender Minority Migrants Across the Migration Trajectory
Bibliographic record
Abstract
Violence against sexual and gender minority (SGM) individuals has continued to proliferate globally. Yet, less is known about victimization among subgroups of SGM individuals, especially SGM immigrants, refugees, and asylum seekers. There has been a steady increase in this vulnerable group of migrants over the years, and emerging evidence has pointed to their heightened risk of victimization. We conducted a scoping review of the peer-reviewed literature that examined violence, abuse, and mental health among SGM individuals who migrate internationally. One hundred ninety-nine articles were identified by searching five scholarly databases and hand searching. Twenty-six articles met inclusion criteria. We first used the migration framework, which outlines the distinct phases of the migration trajectory (predeparture, travel, interception, destination, and return), to categorize findings and then identified four overarching themes to capture SGM migrants’ experiences at each phase: severe and prolonged violence and abuse related to sexual orientation or gender identity (predeparture); continued victimization and high-risk for sexual violence (travel); detainment- and deportation-related violence and abuse (interception and return); and new manifestations of violence and abuse while living with past trauma (destination). Violence and abuse began in childhood and continued in the host country, where they faced discrimination while managing posttraumatic stress disorder and depression. Findings indicate that SGM migrants are extremely vulnerable to victimization. There is an immediate need for policies to protect SGM individuals worldwide and for affirmative, culturally informed practices to help SGM migrants manage trauma and the structural barriers impeding recovery.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.023 | 0.030 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".